Despite recent advancements in modern medicine, disorders involving the central nervous system (CNS) continue to confound the scientific community. Past efforts to treat neurodegenerative conditions like Alzheimer’s disease have met with failure1 and the selective permeability of the blood-brain barrier presents a major difficulty for pharmaucetical development. But with the incidence of brain diseases on the rise, the need for effective CNS drugs has increased.

A recent study found that one-third of all Europeans have at least one type of brain disorder. 2

To successfully treat this growing demographic, pharmaceutical companies must develop more therapies able to cross the blood-brain barrier in sufficient concentrations. Scientists are currently studying novel therapeutics3such as nanoparticle technologies and biologic-delivering exosomes.

One up and coming method is the development of small molecule drugs. Leading researchers have devoted significant resources to identifying promising small molecules that can serve as the foundation for new CNS drugs,4but to take full advantage of this therapeutic technique, pharmaceutical firms must ensure that their data management strategies enable useful insights to aid the discovery of effective small molecule CNS drugs.

The ability to penetrate the blood-brain barrier: To affect disease pathways, potential CNS drugs must be able to cross the membrane. In addition, they need to do so in sufficient concentrations to enact an observable positive result.

The ability to affect a biological target with disease-modifying potential: Any drug development effort requires identifying targets of potential drug action. Understanding how these biological processes lead to disease formation is crucial to creating small molecules able to modify significant pathways.

Despite the clear parameters required for successful CNS drugs, studies delving into the various aspects can yield large amounts of information. Utilizing that knowledge base effectively and efficiently is necessary for drug development, so pharmaceutical companies should adopt data management strategies that streamline the drug discovery process. A few ways to improve data management during the R&D process include:

Improving access to scientific information: Today’s pharmaceutical market has led to the formation of globe-spanning life science organizations. Research collaboration crosses time zones and international borders, making the ability to share data a necessity. Efficient sharing tools allow scientists to identify promising CNS pathways or drug targets for better potential therapies faster.

Screening promising drug candidates: Drug developers can shorten the R&D cycle by screening potential drug candidates using those predictive tools. Drug candidates with better chances of crossing the blood-brain barrier and affecting disease-related pathways can be fast-tracked while small molecules that show no signs of being able to penetrate the membrane can be eliminated from the development process earlier.

Optimizing drug behavior: Once promising small molecule candidates are selected, R&D teams can refine the discovery process by using tools to optimize traits of favorite small molecules. Successful CNS drugs require small molecules be able to cross the membrane and bind to disease-modifying targets in sufficient concentrations to produce a beneficial effect. Being able to improve performance by modifying properties would benefit the development process.

The discovery of a new drug can take years—part of which stems from ineffective data management. To develop CNS drugs able to treat neurodegenerative conditions like Alzheimer’s disease or progressive movement disorders like Parkinson’s disease, pharmaceutical firms must leverage information obtained via experimental research to glean useful insights. By implementing streamlined data management solutions, pharmaceutical companies are able to minimize the time to bring an important CNS drug to market.

Designed to Cure is an industry solution for pharmaceutical companies seeking to streamline the drug discovery process. Its powerful data management tools support collaboration, improve access to crucial knowledge bases, and offer predictive and analytical capabilities. In the quest to develop better CNS drugs faster, life science organizations require the best solutions to support their efforts. If your firm is interested in learning how a digital solution can streamline your drug discovery efforts, please contact us today to learn more.